Bank Opacity Research Articles

PENGARUH OPASITAS BANK TERHADAP TINGKAT PERTUMBUHAN KREDIT DI MODERASI OLEH VARIABEL KAPITALISASI BANK, WHOLESALE FUNDING, MACROECONOMY CONDITION, DAN KUALITAS KREDIT (Studi Empiris pada Bank Umum Konvensional yang terdaftar di BEI 2018-2022)

This study aims to investigate the effect of bank opacity on loan growth rates by considering the role of bank capitalization variables, wholesale funding, macroeconomic conditions, and credit quality as moderating factors. The empirical study was conducted on Conventional Commercial Banks listed on the Indonesia Stock Exchange (IDX) during the period 2018-2022. The research method uses multiple regression analysis and moderation techniques by utilizing financial and macroeconomic data sourced from bank financial reports in Indonesia. The results of this analysis can provide insight into the impact of bank opacity on loan growth, while explaining the extent to which the variables of bank capitalization, wholesale funding, macroeconomic conditions, and credit quality moderate the relationship. The findings of this study are expected to contribute to the understanding of the factors that influence credit growth in the banking sector, particularly in the context of bank opacity. The practical implications of this study can help regulators, bank management, and other stakeholders to develop appropriate policies to improve the stability and growth of the banking sector. Keywords: bank opacity, loan growth, bank capitalization, wholesale funding, macroeconomic conditions, credit quality.

Tác động của tính bất định đến tính không minh bạch của ngân hàng thương mại Việt Nam

The study examines the impact of uncertainty on bank opacity while particularly taking into account the moderating role of market structures. Using a sample of Vietnamese banks from 2007 to 2019, the paper measures uncertainty at the disaggregate level of the banking sector through the dispersion of bank shocks and regresses the bank opacity. The research introduces both structural and non-structural proxies of bank competition/concentration to better explore the role of market structures. Empirical regressions are conducted using the two-step system generalized method of moments (GMM) technique, and then verified by the least squares dummy variable corrected (LSDVC) estimator. The research result suggests that bank earnings opacity is less severe in periods of higher uncertainty. This implies that banks in a competitive markets need to reduce information asymmetry and more transparent in uncertainty.

Bank opacity, systemic risk and financial stability

This paper examines the impact of bank opacity on European financial stability. Based on a panel dataset of listed European banks covering the period 2002–2018, I find that bank opacity has a significant influence on the institution-specific contribution to the ∆Conditional Value at Risk and Marginal Expected Shortfall. The enforcement mechanism and the policies introduced by accounting standard setters and regulators for the risk disclosure of banks have a positive impact on the reduction of systemic risk. Both the risk reporting in accordance with IFRS 7 and the measures introduced by the Basel Committee in the form of the Basel Pillar 3 regulation led to an increase in transparency and thus an improvement in financial market stability. As an independent enforcement mechanism, the country-specific strength of the external auditing profession plays a significant role in fostering stability. The results are robust, by using both alternative opacity measures and instrumental-variable estimations (2SLS) to control for potential endogeneity.

Bank Opacity and Risk-Taking: The Moderating Role of Competition

Bank Opacity and Risk-Taking: The Moderating Role of Competition

Internal ratings and bank opacity: Evidence from analysts’ forecasts

We document that reliance on internal ratings-based (IRB) models to compute credit risk and capital requirements reduces bank opacity. Greater reliance on IRB models is associated with lower absolute forecast error and reduced disagreement among analysts regarding expected bank earnings per share. These results are stronger for banks that apply internal ratings to the most opaque loans and adopt the advanced version of IRB models, which entail a more granular risk assessment and greater disclosure of risk parameters. The results stem from the higher earnings informativeness and the more comprehensive disclosure of credit risk in banks adopting internal ratings. We employ an instrumental variables approach to validate our findings.

Societal trust and bank opacity

PurposeThis paper aims to examine the relationship between societal trust and bank asset opacity using an international sample of banks.Design/methodology/approachThe authors use an international data set of banks and panel regressions. For robustness purposes, the authors use multiple measures of both societal trust and bank opacity as well as two-stage least squares regressions to address endogeneity concerns.FindingsThe authors find that societal trust is negatively associated with the opacity of bank portfolios.Practical implicationsResults of this study inform regulators on the importance of trust for the banking sector and support policies towards enhancing trust in banks. Also, a sustained environment of high levels of trust in banks can prevent the introduction of extensive prudential regulations that policymakers often use to establish trust, as well as lower the additional resources required when trust levels are low.Originality/valueTo the best of the authors’ knowledge, this is the first study that examines this relationship. The literature provides only limited evidence and not for the banking sector, for which opacity is of outmost importance.

Machine learning in bank merger prediction: A text-based approach

This paper investigates the role of textual information in a U.S. bank merger prediction task. Our intuition behind this approach is that text could reduce bank opacity and allow us to understand better the strategic options of banking firms. We retrieve textual information from bank annual reports using a sample of 9,207 U.S. bank-year observations during the period 1994-2016. To predict bidders and targets, we use textual information along with financial variables as inputs to several machine learning models. We find that when we jointly use textual information and financial variables as inputs, the performance of our models is substantially improved compared to models using a single type of input. Furthermore, we find that the performance improvement due to the inclusion of text is more noticeable in predicting future bidders, a task which is less explored in the relevant literature. Therefore, our findings highlight the importance of textual information in a bank merger prediction task.

Bank opacity and stability in an emerging market

PurposeThe paper analyzes the impact of bank opacity on financial stability in an emerging economy.Design/methodology/approachBased on a unique dataset of 31 Vietnamese commercial banks from 2007 to 2019, the paper captures earnings opacity via discretionary loan loss provisions and reflects individual bank stability through the accounting-based Z-score index and its disaggregate components. The least squares dummy variable corrected (LSDVC) approach is employed for empirical analysis.FindingsIn contradiction to most studies on developed economies, earnings management improves bank financial stability in Vietnam. Earnings management is more important for the financial stability of smaller banks. Further, the effect of financial information disclosure on bank stability is strengthened by unfavorable macroeconomic conditions, particularly economic downturns, the global financial crisis and uncertain times in banking.Originality/valueThis is the first study to shed light on how bank opacity influences bank financial stability in an emerging market. The evidence with the conditioning roles of bank size and macroeconomic factors, such as uncertainty in banking, is entirely novel in the related literature. Additionally, the paper contributes to a growing body of banking literature by using the LSDVC estimator to examine the association between bank opacity and bank stability.

Assessing the financial and informational role of supervisory stress tests: EU-wide 2018 stress test vis-à-vis EU-wide 2021 stress test

PurposeThe supervisory stress test evaluates the capital adequacy and profit-generation capacity of systemic banking institutions under baseline and adverse macroeconomic scenarios. This study aims to assess the financial and informational role of European stress tests and substantiate the impact of their disclosures by examining the EU-wide 2018 stress test vis-à-vis the EU-wide 2021 stress test in terms of how and to what extent the stock prices of the stress-tested banks have been affected.Design/methodology/approachThis study applies standard event study methodologies to evaluate the reactions of market participants during the EU-wide 2018 and 2021 stress test exercises. We examine several “large” events in both the exercises for a selected sample of European banks.FindingsThe results of our event study analysis show that the EU-wide 2018 and 2021 stress tests come subsequent to considerable abnormal price movements. The announcement of stress test results triggered tangible investor reactions, indicating the informational value of stress tests in reducing bank opacity. This supervisory “toolkit” is considered extremely important, as it provides meaningful insights to the supervisors of the banking institutions and the market stakeholders by improving the transparency of the financial sector, allowing them to segregate banks more effectively.Originality/valueThis study constitutes one of the earliest attempts to shed light on the financial and information role of the European supervisory stress tests by comparing the EU-wide 2018 and the EU-wide 2021 stress test exercises. Moreover, it provides concrete empirical evidence and qualitative analysis to explore certain aspects of the European and US stress tests.

Internal Ratings, Non-Performing Loans, and Bank Opacity: Evidence from Analysts’ Forecasts

We use a panel data set of large listed European banks to evaluate the effect of the usage of internal ratings-based (IRB) models on bank opacity. We find that a more intensive usage of these models is associated with lower forecast error and disagreement among analysts about bank earnings per share. These results seem to be driven by the more detailed disclosure of loan portfolios required of IRB users, and are stronger in banks adopting the advanced version of IRB models. In these banks the negative effect of non-performing loans on bank transparency is mitigated. However, the transparency-enhancing role of IRB models fades in low-capital banks, suggesting that capital constraints could favor an opportunistic usage of internal ratings that counterbalances their beneficial effect on bank transparency.

The Impact of Technology-Driven M&A on Bank Opacity, Stock Price Synchronicity, and Risk Composition: Empirical Evidence from Japan and a Causality Analysis

The Impact of Technology-Driven M&A on Bank Opacity, Stock Price Synchronicity, and Risk Composition: Empirical Evidence from Japan and a Causality Analysis

Bank Opacity and Safe Asset Moneyness

Bank Opacity and Safe Asset Moneyness

Uncertainty, bank opacity, and market structure

PurposeThe study examines the impact of uncertainty on bank opacity while particularly taking into account the moderating role of market structures.Design/methodology/approachUsing a sample of Vietnamese banks from 2007 to 2019, the paper measures uncertainty at the disaggregate level of the banking sector through the dispersion of bank shocks and capture bank opacity from the perspective of bank earnings management based on discretionary loan loss provisions. The authors apply both structural and non-structural proxies of bank competition/concentration to better explore the role of market structures. Empirical regressions are conducted using the fixed effect regressions with Driscoll–Kraay standard errors and the two-step system generalized method of moments (GMM) technique, and then verified by the least squares dummy variable corrected (LSDVC) estimator.FindingsBank earnings opacity is less severe in periods of higher uncertainty. Further analysis documents that the negative impact of uncertainty on bank earnings opacity is stronger when the level of bank competition increases or when bank market power decreases.Originality/valueThe finding highlighting the conditioning role of market structures is entirely novel in the uncertainty-bank opacity literature. Moreover, in providing additional evidence on the significant impact of uncertainty on bank opacity, while prior related studies explore economic policy uncertainty, the authors utilize micro uncertainty in banking that exhibits enormous superiority.

The dark side of liquidity regulation: Bank opacity and funding liquidity risk

We evaluate how the liquidity coverage rule affects US banks’ opacity and funding liquidity risk. Banks subject to the rule become significantly more opaque and funding liquidity risk increases by $245 million per quarter. Higher funding liquidity risk is more pronounced among banks that are subject to the rule’s more stringent liquidity buffers, and systemically riskier banks. Rising opacity reflects an increase in banks’ holdings of complex assets whose value is difficult to communicate to investors. The evidence highlights the unintended consequences of liquidity regulation and is consistent with theoretical models’ predictions of a trade-off between liquidity buffers and bank opacity that exacerbates funding liquidity risk.

THE IMPACT OF RESERVES PRACTICES ON BANK OPACITY

This paper finds that banking firms’ unexpected loan loss provisions had a significant effect of increasing bank opacity, both before and during the 2007–2009 financial crisis. Furthermore, during the financial crisis, the extent to which banks delayed loan loss recognition is found to have had a significant effect on bank opacity, confirming an important concern raised by the Financial Crisis Advisory Group. Overall, banks’ practices in managing reserves seem to have a material impact on their opacity.

The impact of bank opacity on bank risk‐taking behavior

AbstractWe examine the impact of opacity on bank stability using a large US bank sample from 2001 to 2021. We observe that increasing opacity erodes bank stability. Our results indicate that the spillover effects of opacity induce greater price synchronicity and consequently increase systematic risk. These stability‐destroying effects of bank opacity are transferred via reduced profitability, deteriorated asset quality, and increased earnings volatility. The negative effects of opacity on bank stability are more pronounced in financially stronger and larger banks. They are muted in dividend‐paying banks. This study supports the concerns of prior researchers over too‐big‐to‐fail institutions and should be of interest to policymakers and other bank stakeholders.

Regulatory arbitrage, bank opacity and risk taking in Chinese shadow banking from the perspective of wealth management products

We set up a general equilibrium model of Chinese wealth management products (WMPs), which are deeply rooted in traditional Chinese commercial banks. According to this model, we proposed two hypotheses, namely, the regulatory arbitrage and information asymmetry hypotheses. We tested the hypotheses by using data on Chinese WMPs during the 2006–2015 period. We found that regulatory arbitrage was the main driver of WMPs’ rapid expansion. The greater the pressure from regulation was, the greater the incentive for commercial banks to issue off-balance sheet WMPs and take risks. When the regulatory standard became strict or loose, the effect of regulatory arbitrage on marginal risk-taking behavior became reinforced or reduced, respectively. We also argue that transparency can moderate drive-up behavior. Some relevant suggestions are provided for solving the problems of overexpansion and risk-taking behavior according to the results.

The politics of bank opacity

The distribution of power in the political system shapes the financial reporting opacity of banks. Specifically, banks located in states with senators on the Senate Banking Committee (BC senators) have greater abnormal loan loss provisions than banks in other states. The result is stronger for larger banks and banks with higher risk. In addition, BC senators have a negative effect on the likelihood of banks in their home states receiving enforcement actions, and, more importantly, this effect is stronger for more opaque banks. These findings suggest that politicians, regulators, and banks use opaque financial reporting to facilitate regulatory forbearance. Moreover, we show that opacity is a significant channel through which BC senators increase bank risk. During economic downturns, however, BC senators appear to promote bank opacity to encourage bank lending and create liquidity. Finally, the capital market does not penalize the reporting opacity of banks in states with BC senators.

Bank risk and charter value: the role of opacity

In this paper, we explore the linkage between bank opacity and bank charter value. We find that opacity contaminates charter value and therefore reduces the ability of charter value to restrain risk-taking in banking. As bank assets become more complex and opaque with the increased use of derivative assets like mortgage backed securities, asset backed securities, and collateralised debt obligations, etc., it becomes more difficult to gauge the true value of banks and the true risk of the bank activities.

Machine learning in U.S. Bank Merger Prediction: A Text-Based Approach

This paper investigates the role of textual information in a U.S. bank merger prediction task. Our intuition behind this approach is that text could reduce bank opacity and allow us to understand better the strategic options of banking firms. We retrieve textual information from bank annual reports using a sample of 9,207 U.S. bank-year observations during the period 1994-2016. To predict bidders and targets, we use textual information along with financial variables as inputs to several machine learning models. Our key findings suggest that: (1) when textual information is used as a single type of input, the predictive accuracy of our models is similar, or even better, compared to the models using only financial variables as inputs, and (2) when we jointly use textual information and financial variables as inputs, the predictive accuracy of our models is substantially improved compared to models using a single type of input. Therefore, our findings highlight the importance of textual information in a bank merger prediction task.